Publications

In this work, we introduce and compare the results of several methods for determining the horizon profile at a PV site, and compare their use cases and limitations. The methods in this paper include horizon detection from time-series irradiance or performance data, modeling from GIS topology data, manual theodolite measurements, and camera-based horizon detection. We compare various combinations of these methods using data from 4 Regional Test Center sites in the US, and 3 World Bank sites in Nepal. The results show many differences between these methods, and we recommend the most practical solutions for various use-cases.

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This article presents a notable advance toward the development of a new method of increasing the single-axis tracking photovoltaic (PV) system power output by improving the determination and near-term prediction of the optimum module tilt angle. The tilt angle of the plane receiving the greatest total irradiance changes with Sun position and atmospheric conditions including cloud formation and movement, aerosols, and particulate loading, as well as varying albedo within a module's field of view. In this article, we present a multi-input convolutional neural network that can create a profile of plane-of-array irradiance versus surface tilt angle over a full 180^{\circ } arc from horizon to horizon. As input, the neural network uses the calculated solar position and clear-sky irradiance values, along with sky images. The target irradiance values are provided by the multiplanar irradiance sensor (MPIS). In order to account for varying irradiance conditions, the MPIS signal is normalized by the theoretical clear-sky global horizontal irradiance. Using this information, the neural network outputs an N-dimensional vector, where N is the number of points to approximate the MPIS curve via Fourier resampling. The output vector of the model is smoothed with a Gaussian kernel to account for error in the downsamping and subsequent upsampling steps, as well as to smooth the unconstrained output of the model. These profiles may be used to perform near-term prediction of angular irradiance, which can then inform the movement of a PV tracker.

Cell cracking in PV modules can lead to a variety of changes in module operation, with vastly different performance degradation based on the type and severity of the cracks. In this work, we demonstrate automated measurement of cell crack properties from electroluminescence images, and correlate these properties with current-voltage curve features on 35 four-cell Al-BSF and PERC mini-modules showing a range of crack types and severity. Power loss in PERC modules was associated with more total crack length, resulting in electrical isolation of cell areas and mild shunting and recombination. Many of the Al-BSF modules suffered catastrophic power loss due to crack-related shunts. Mild power loss in Al-BSF modules was not as strongly correlated with total crack length; instead crack angles and branching were better indicators of module performance for this cell type.

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